add vllm_dtype arg #3387 #3717

src/llamafactory/chat/vllm_engine.py

@@ -3,7 +3,7 @@ from typing import TYPE_CHECKING, AsyncGenerator, AsyncIterator, Dict, List, Opt
 
 from ..data import get_template_and_fix_tokenizer
 from ..extras.logging import get_logger
-from ..extras.misc import get_device_count, infer_optim_dtype
+from ..extras.misc import get_device_count
 from ..extras.packages import is_vllm_available
 from ..model import load_config, load_tokenizer
 from ..model.utils.visual import LlavaMultiModalProjectorForYiVLForVLLM
@@ -35,8 +35,6 @@ class VllmEngine(BaseEngine):
         generating_args: "GeneratingArguments",
     ) -> None:
         config = load_config(model_args)  # may download model from ms hub
-        infer_dtype = infer_optim_dtype(model_dtype=getattr(config, "torch_dtype", None))
-        infer_dtype = str(infer_dtype).split(".")[-1]
 
         self.can_generate = finetuning_args.stage == "sft"
         tokenizer_module = load_tokenizer(model_args)
@@ -50,7 +48,7 @@ class VllmEngine(BaseEngine):
             "model": model_args.model_name_or_path,
             "trust_remote_code": True,
             "download_dir": model_args.cache_dir,
-            "dtype": infer_dtype,
+            "dtype": model_args.vllm_dtype,
             "max_model_len": model_args.vllm_maxlen,
             "tensor_parallel_size": get_device_count() or 1,
             "gpu_memory_utilization": model_args.vllm_gpu_util,
@@ -70,7 +68,6 @@ class VllmEngine(BaseEngine):
             engine_args["image_input_shape"] = "1,3,{},{}".format(image_size, image_size)
             engine_args["image_feature_size"] = self.image_feature_size
             if getattr(config, "is_yi_vl_derived_model", None):
-                # bug in vllm 0.4.2, see: https://github.com/vllm-project/vllm/pull/4828
                 import vllm.model_executor.models.llava
 
                 logger.info("Detected Yi-VL model, applying projector patch.")

src/llamafactory/hparams/model_args.py

@@ -125,6 +125,10 @@ class ModelArguments:
         default=8,
         metadata={"help": "Maximum rank of all LoRAs in the vLLM engine."},
     )
+    vllm_dtype: Literal["auto", "float16", "bfloat16", "float32"] = field(
+        default="auto",
+        metadata={"help": "Data type for model weights and activations in the vLLM engine."},
+    )
     offload_folder: str = field(
         default="offload",
         metadata={"help": "Path to offload model weights."},